Real-time cardiovascular MRI and co-registration technical development

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During the past year we have continued enhancement of imaging platforms to guide cardiovascular catheter based treatments. These have included co-registered MRI with conventional X-ray, as well as standalone real-time MRI. Static 3D roadmaps derived from MRI datasets are used to enhance image guidance for X-ray cardiovascular interventional procedures, and indeed have been used in this lab to develop novel treatments such as mitral cerclage annuloplasty. Static roadmaps do not accurately represent cardiovascular anatomy during cardiac and respiratory motion. We have developed a system to measure respiratory and cardiac motion from real-time MRI scans and to derive a set of affine models which can be used to beat and breath the 3D roadmaps overlaid on live X-ray. We also have developed robust fully automatic mathematical techniques to register fiducial markers between imaging modalities. We will continue to improve the workflow and usability of the system so that it can be used on a routine basis to guide procedures. We plan to apply this systematically to pediatric and adult catheterization procedures in the coming years. We have developed a system of adaptive noise cancellation to filter out interference from the radiofrequency and magnetic gradient fields in an MRI suite, and demonstrated the ability to detect arrhythmia otherwise obscured during MR scanning. We have expanded the system to full multiple lead surface and intracardiac electrograms, to integrated this into a clinical hemodynamic recording system during investigational MRI-guided catheterization. We will continue to enhance this system to accomodate high-risk clinical workflows, including an MRI-compatible wireless telemetry system. We have used inexpensive parallel computing resources afforded by game-oriented Graphics Processing Units to accelerate reconstruction of computationally-intensive MRI data. We have successfully integrated non-Cartesian parallel imaging in an interactive acquisition and reconstruction setup and demonstrated that real-time reconstruction and visualization is possible for relatively complicated reconstruction algorithms. This has been integrated with the scanner software to allow seamless combination with other sequence components. We have developed a system to provide the operator multiple simultaneous representations of real-time MRI data balancing temporal and spatial resolution interactively. The operator chooses the desired representation. We have implemented golden-angle real-time MRI with interactive selection of the temporal resolution. We are migrating our highly successful local real-time MRI software environment onto a commercial platform to facilitate translation outside of NIH, and to enhance industry and university collaboration. This has required considerable development to update workhorse real-time MRI pulse sequences to facilitate rapid multi-author or multi-institution prototyping. This development has allowed investigational human MRI catheterization to be performed with the staff support of a technologist rather than a physicist, reflecting a polished and clinically-relevant system. We also continue to develop new approaches to real-time MRI, or to engineer local noncommercial embodiments of real-time MRI to suit the needs of procedures being developed.